Wireless communication technology has become a critical aspect in many civilian and military applications. With regard to remote sensing, search and rescue, and disaster relief operations, there exists an interest in developing capabilities to collect these signals-of-interest.
With the increased use of unmanned aerial vehicles (UAVs) in military and civilian applications, researchers and major companies are beginning to push for their adoption into wireless sensor networks (WSNs). Recently, large-scale, high altitude wireless networks have been proposed to provide internet access to undeveloped regions. One notable project hopes to deliver internet access via a wireless network of UAVs. This network consists of large scale UAVs deployed at an altitude of 20 km (see References 1 and 2). Another concept uses a single high altitude UAV in conjunction with a concentric circle WSN formation to enhance network to sink connectivity (see Reference 3). Operating at a smaller scale and altitude, multirotor UAVs can also deliver similar capabilities at a much lower price point (see Reference 4).
Beamforming has been shown to be an effective method for signal collection and interference rejection (see Reference 5), but it has been shown to be highly susceptible to array steering vector errors (see Reference 6). This is when an array steering vector is not in line with that of the target signal. To make beamforming more robust against these array mismatch errors, Ahmed and Evans (see Reference 7) suggest the use of inequality constraints on the array weights. Lee and Lee (see Reference 8) proposed a robust beamformer for signal collection, which minimizes a cost function based on received signal data and knowledge of steering error statistics.